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Jd bias scrubber

Skill SkillMedev/people-ops-recruiting/skills/jd-bias-scrubber

Hire, onboard, and run a team fairly — without a full HR department.

Install
npx -y skills add SkillMedev/people-ops-recruiting --skill jd-bias-scrubber

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Audits a job description for exclusionary, gendered, age-coded, ableist, and pedigree-gatekeeping language and returns a findings table with neutral rewrites and severity. Use when drafting, reviewing, or auditing a job posting or JD before it is published, when asked to check a role description for biased or non-inclusive wording, or before a requisition goes to a job board.

SKILL.md

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JD Bias Scrubber

Surface words and requirements in a job description that deter qualified candidates without adding predictive value, and propose neutral rewrites the hiring manager can accept or reject. You flag; you never silently rewrite intent. Remember the asymmetry the audit exists to correct: a widely cited internal HP study found women tend to apply only when they meet ~100% of listed requirements while men apply at ~60% - every unnecessary requirement shrinks the pool unevenly.

Workflow

  1. Scan for gender-coded language. Flag masculine-coded terms ("dominant," "aggressive," "rockstar," "crush it," "competitive," "ninja") and feminine-coded terms that skew the pool; propose role-relevant neutral phrasing ("sets a high bar," "delivers results"). Flag pronoun assumptions and replace with "you" or the role title.
  2. Catch age and experience coding. Flag "digital native," "recent grad," "high energy," "young team," and maximums like "no more than 5 years." Question any years-of-experience minimum above what the work requires - minimums above 5 years rarely map to competency for non-executive roles; convert them to the actual competency or a soft range, since high minimums screen out career changers and returners.
  3. Surface ableist and physical-demand language. Flag "able-bodied," blanket "must stand for hours," and "fast-paced high-pressure" used as a personality filter. Flag metaphors ("see," "walk," "strong") when not literal job functions. Where a physical demand is genuine, state it precisely and pair it with an accommodation note instead of a blanket exclusion.
  4. Question credential and pedigree gatekeeping. Flag degree requirements, "top university," "Big Tech experience," and citizenship/native-speaker phrasing that exceed legal or job need. Suggest the demonstrable skill instead. Flag "native English speaker" as possible national-origin discrimination; prefer "fluent professional English." Flag a required-qualifications list longer than 5-7 items: recommend demoting the rest to "nice to have."
  5. Output the findings table. Return one row per flagged phrase with columns: flagged phrase, why it may exclude, suggested neutral alternative, severity (legal-risk / pool-shrinking / tone). Preserve substantive requirements; challenge only those with no job-relevant basis.

Deliverable

Produce the findings table - one row per flagged phrase with the phrase, why it may exclude, a usable neutral rewrite, and severity - topped by a two-line summary: total flags by severity, and whether the JD is publishable once legal-risk rewrites are accepted or explicitly waived by counsel.

Quality bar

  • Every flag names the specific phrase and a concrete reason it excludes or carries risk - no generic "this could be biased."
  • Every flag pairs with a usable neutral rewrite, not just a deletion.
  • Severity is assigned to each row so the hiring manager can triage legal-risk items first.
  • Substantive, job-relevant requirements are left intact and untouched.
  • For high-severity (legal-risk) items, phrase risk as "may raise EEOC / ADA / ADEA risk" and recommend counsel review.

Do NOT

  • Do NOT assert a phrase is definitively illegal - you are an advisory pass, not an approver, and a human owns final wording and legal review.
  • Do NOT silently rewrite the JD; return findings the hiring manager accepts or rejects.
  • Do NOT strip or soften genuine, job-relevant requirements to chase neutrality.
  • Do NOT use a candidate's name, an applicant's traits, or any protected characteristic in your analysis - you assess the text, not people.
  • Do NOT use this to screen resumes, evaluate applicants, or do general copyediting - this audits the job posting's language only.

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